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Machine Learning in the ICU: Predicting Mortality in Bloodstream Infections (ICU:Intensive Care Unit)

NCT06167083 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 197

Last updated 2026-03-11

No results posted yet for this study

Summary

Using our own patient data, our study aimed to predict mortality that can develop in Carbapenem-resistant Gram-negative bacilli bloodstream infections with a machine learning-based model.

In the intensive care unit, patients with bloodstream infections, both with and without mortality, will be examined retrospectively in two subgroups for comparison.

Conditions

  • Carbapenem Resistant Bacterial Infection

Interventions

DIAGNOSTIC_TEST

Machine Learning to Estimate Mortality

Using deep learning we try to develop an algorithm and anticipate mortality

Sponsors & Collaborators

  • Kocaeli University

    lead OTHER

Principal Investigators

  • özlem güler · Kocaeli University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-04-12
Primary Completion
2025-06-28
Completion
2025-06-28

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06167083 on ClinicalTrials.gov